ASML's $400 million next-generation chipmaking machine explained
MIT Technology Review profiles ASML's latest extreme ultraviolet (EUV) lithography machine, a 150-ton, $400 million system that represents the leading edge of semiconductor manufacturing capability. The piece centers on ASML's role as the sole supplier of EUV equipment critical to producing the most advanced chips. This is directly relevant to AI infrastructure as frontier AI training and inference depend on the most advanced semiconductor nodes that only ASML's machines can produce.
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Mistral AI Raises €1.7B Series C at €11.7B Valuation, Led by ASML
Mistral AI has closed a €1.7 billion Series C funding round at an €11.7 billion post-money valuation, led by semiconductor equipment giant ASML Holding NV. The round includes participation from existing investors DST Global, Andreessen Horowitz, Bpifrance, General Catalyst, Index Ventures, Lightspeed, and NVIDIA. The partnership with ASML is framed around developing AI solutions for semiconductor and industrial engineering challenges. Mistral emphasizes continued independence and focus on custom, decentralized frontier AI for strategic industries.
Meta Announces Four MTIA AI Chip Generations in Two Years: MTIA 300–500 Roadmap
Meta has detailed a rapid four-generation MTIA chip roadmap (300, 400, 450, 500) developed in partnership with Broadcom, spanning ranking/recommendation inference and training through general GenAI workloads. Key advances include a 4.5x HBM bandwidth increase and 25x compute FLOPS improvement from MTIA 300 to 500, with MTIA 450 and 500 targeting GenAI inference with doubled and further-increased HBM bandwidth versus leading commercial products. MTIA 300 is in production for R&R training, MTIA 400 is lab-tested and entering deployment, while MTIA 450 and 500 are scheduled for mass deployment in early 2027 and 2027 respectively. The strategy emphasizes modular chiplet design and short iteration cycles to keep hardware aligned with rapidly evolving AI model requirements.
Anthropic and Amazon Expand Collaboration for Up to 5 Gigawatts of New Compute
Anthropic has signed a major expanded agreement with Amazon committing over $100 billion to AWS technologies over ten years, securing up to 5GW of compute capacity for training and deploying Claude across Trainium2 through Trainium4 chips. Amazon is investing an additional $5 billion in Anthropic today, with up to $20 billion more possible in the future, building on $8 billion previously invested. The deal includes nearly 1GW of Trainium2 and Trainium3 capacity coming online by end of 2026, expanded inference in Asia and Europe, and the full Claude Platform becoming available directly within AWS. Anthropic disclosed its run-rate revenue has surpassed $30 billion, up from approximately $9 billion at end of 2025.
OpenAI unveils first custom AI chip, manufactured by Broadcom
OpenAI has announced its first custom silicon chip, built in partnership with Broadcom. This marks a significant strategic move for OpenAI to reduce dependence on Nvidia and control its own inference and training infrastructure. Custom chip development is a major capital and engineering commitment that signals OpenAI's long-term infrastructure ambitions.
Nvidia's AI Systems Design Chip Circuits, Verify Designs, and Test New Layouts
Nvidia chief scientist Bill Dally described the company's use of AI across five stages of chip design at GTC 2025, including NVCell (a RL+genetic algorithm system that redesigns ~2,500-3,000 layout cells overnight vs. 10 engineer-months), PrefixRL (RL-designed arithmetic circuits 20-30% better than human designs), and ChipNeMo/BugNeMo (LLaMA 2-based LLMs fine-tuned on internal GPU documentation). The systems demonstrate measurable improvements over human and industry-standard designs, though Dally acknowledged that fully autonomous GPU design from a prompt remains a distant goal. The piece also references a 2025 Verkoran paper describing an agentic system that autonomously designed a RISC-V CPU from a 219-word specification.
Microsoft, NVIDIA, and Anthropic Announce Major Strategic Partnerships with $15B Investment and $30B Azure Compute Commitment
Anthropic has announced simultaneous strategic partnerships with Microsoft and NVIDIA, committing to purchase $30 billion of Azure compute capacity and up to one gigawatt of compute with NVIDIA Grace Blackwell and Vera Rubin systems. NVIDIA and Microsoft are investing up to $10 billion and $5 billion respectively in Anthropic, while Claude models (Sonnet 4.5, Opus 4.1, Haiku 4.5) will be available on Microsoft Foundry and across the Copilot product family. Anthropic and NVIDIA are also establishing a deep technology partnership to co-optimize model performance and future NVIDIA architectures for Anthropic workloads. Amazon remains Anthropic's primary cloud and training partner.
Anthropic Expands Partnership with Google and Broadcom for Multi-Gigawatt TPU Compute Capacity
Anthropic has signed a new agreement with Google and Broadcom for multiple gigawatts of next-generation TPU capacity expected to come online starting in 2027, representing the company's largest compute commitment to date. The announcement coincides with Anthropic reporting run-rate revenue surpassing $30 billion, up from ~$9 billion at end of 2025, and the number of enterprise customers spending over $1M annually doubling to 1,000+ in under two months. The compute will be predominantly US-sited, extending Anthropic's November 2025 $50B American infrastructure commitment. Anthropic continues to operate across AWS Trainium, Google TPUs, and NVIDIA GPUs, with Amazon remaining its primary cloud and training partner.
SmolVLM Grows Smaller – Introducing the 256M & 500M Models
Hugging Face has released two new ultra-compact vision-language models, SmolVLM-256M and SmolVLM-500M, extending the SmolVLM family to sub-billion parameter sizes. These models are designed for on-device and resource-constrained deployment scenarios. The release continues the trend of pushing capable multimodal models into smaller footprints suitable for edge inference.